WHO YOU’LL WORK WITH
You’ll be working with McKinsey’s Operations practice in Europe. Our Operations practice assists our clients in solving complex operational challenges. Blending strategic thinking with hands-on practicality, our teams of consultants and experts work to develop and implement operational strategies that solve our clients' most critical problems.
As part of our Operations practice, our Advanced Analytics teams bring the latest analytical techniques plus a deep understanding of industry dynamics and corporate functions to help clients create the most value from data. Advanced analytics can help solve problems in optimization, forecasting, simulation, and big data comparison and visualization. Combining deep strategic and business insight with world-class technological and operational capabilities, we work with clients to identify where to focus their efforts, convert data and models into actionable insights, and develop institutional skills and structures to sustain impact.
WHAT YOU’LL DO
You’ll serve as an engineering or production expert on consultant teams that lead McKinsey clients to higher levels of operating performance.
You will be instrumental in the analysis of client requirements as well as in the design and implementation of programs to transform clients' operations. Furthermore, you will develop specific solutions by working in close collaboration with client-based experts and executives.
The challenges you will face range from the implementation of shop-floor improvements to fundamental changes in work processes and information and material flows. In addition to working directly with clients, you will also exchange knowledge with colleagues at the international level and contribute to developing both your own and our expertise, and refining our approaches in the areas of maintenance and lean production.
- Comprehensive practical knowledge in the field of maintenance, repairs, and equipment reliability, ideally gained in a process industry or similarly capital-intensive sector
- Familiarity with standard tools for improving maintenance efficiency and effectiveness, e.g., planning and managing maintenance work, preventive and prospective maintenance and equipment care
- Ideally, first-hand experience with advanced analytical methods for reliability-related improvement (predictive maintenance) and a basic understanding of machine-learning techniques (e.g., neural networks)
- Advanced graduate degree and excellent academic record required (e.g., Master, MBA, PhD, etc.)
- Ability to work collaboratively in a team environment
- Strong record of leadership in an academic, professional, or extracurricular setting
- Mobile and excited to take on longer international assignments
- Ability to communicate complex ideas effectively, both verbally and in writing, in English and the local office language(s)